During the combustion process, gasoline is oxidized and hydrogen (H) and carbon (C) combine with air. Various chemical compounds are formed including carbon dioxide (CO2), water (H2O), carbon monoxide (CO), nitrogen oxides (NOx), unburned hydrocarbons (HC), sulfur oxides (SOx), and other compounds. Automobile exhaust systems include a catalytic converter that reduces the levels of CO, HC, and NOx in the exhaust gas by chemically converting these gasses into carbon dioxide, nitrogen, and water. Diagnostic regulations require periodic monitoring of the catalytic converter for proper conversion capability.
Typical monitoring methods employ two exhaust gas oxygen sensors and infer the conversion capability of the catalytic converter using the sensor signals. One sensor monitors the oxygen level associated with an inlet exhaust stream of the catalytic converter. This inlet O2 sensor is also the primary feedback mechanism that maintains the fuel-to-air (F/A) ratio of the engine at the chemically correct, or stoichiometric F/A ratio needed to support the catalytic conversion processes. A second or outlet O2 sensor monitors the oxygen level concentration of the exhaust stream exiting the catalytic converter.
Traditional monitoring methods relate the empirical relationships that exist between the inlet and outlet O2 sensor to quantify catalyst conversion capability. These methods compare sensor amplitude, response time, response rate, and/or frequency content data. All of these measurements are affected by a property of a catalytic converter known as Oxygen Storage Capacity (OSC). OSC refers to the ability of a catalytic converter to store excess oxygen under lean conditions and to release oxygen under rich conditions. The amount of oxygen storage and release decreases as the conversion capability of the catalytic converter is reduced. Therefore, the loss in OSC is related to the loss in conversion capability.
Traditional methods for diagnosing catalytic converter performance based on OSC are intrusive. More specifically, traditional diagnostic methods manipulate the F/A ratio and monitor the resultant sensor signal.